activity
20152023
most citedFully Distributed Multi-Robot Collision Avoidance via Deep Reinforcement Learning for Safe and Efficient Navigation in Complex Scenarios

69 citations · 335 across the 44 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

cs.RO2020★ 1 cited

Design of an Optoelectronically Innervated Gripper for Rigid-Soft Interactive Grasping

Linhan Yang, Xudong Han, Weijie Guo +4

Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust graspi…

cs.RO2020★ 2 cited

Optimization-Based Framework for Excavation Trajectory Generation

Yajue Yang, Pinxin Long, Jia Pan +2

In this paper, we present a novel optimization-based framework for autonomous excavator trajectory generation under various objectives, including minimum joint displacement and min…

cs.RO2020★ 3 cited

Autonomous Social Distancing in Urban Environments using a Quadruped Robot

Tingxiang Fan, Zhiming Chen, Xuan Zhao +5

COVID-19 pandemic has become a global challenge faced by people all over the world. Social distancing has been proved to be an effective practice to reduce the spread of COVID-19.…

cs.RO2020★ 8 cited

Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator

Yajue Yang, Jia Pan, Pinxin Long +2

In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates th…

cs.CV2020★ 1 cited

Keyfilter-Aware Real-Time UAV Object Tracking

Yiming Li, Changhong Fu, Ziyuan Huang +2

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter…

cs.RO2020★ 24 cited

Rigid-Soft Interactive Learning for Robust Grasping

Linhan Yang, Fang Wan, Haokun Wang +4

Inspired by widely used soft fingers on grasping, we propose a method of rigid-soft interactive learning, aiming at reducing the time of data collection. In this paper, we classify…